1. On the relationship between the observed dynamics of a colorimetric indicator and the nonlinear dynamics of the population growth under study in the case of microbial cultures
- Author
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Sychev, Alexander Владимирович and Postnikov, Eugene B
- Subjects
resazurin ,resorufin ,cellular activity ,population dynamics ,Physics ,QC1-999 - Abstract
The resazurin test is one of the most widespread approaches for studying the growth and metabolic activity of microorganisms. It is based on the colour change of the blue indicator, resazurin, to its pink reduced form, resorufin due to the reduction process catalyzed by the metabolic activity. At the same time, the quantitative characterization of the process needs to take into account the fact that one registers the results of the chemical transformation, which can differ from the underlying kinetics of the population growth. Purpose. The principal goal of this work is a sequential modelling of both coupled nonlinear growth processes aimed at obtaining the closed-form solution depending on the specificity and parameters of biological and chemical counterparts and its comparison with the curves obtained experimentally. Methods. The indicator concentration change is derived under the assumption of the logistic bacterial growth catalyzing the unidirectional chemical reaction considered and compared with the photometrically registered growth curve for a population of lactobacteria. Results. It is revealed that the biochemical growth curve will be logistic too only in the case of specially coordinated kinetic parameters and the systems’ carrying capacity. Otherwise, another functional form should be used to approximate the observable dynamics. Conclusion. Thus, the main conclusion consists of drawing attention to the importance of distinguishing between the underlying microbial and observable chemical growth curves. Their difference affects the value of the population growth rate, which is the target of such tests, and, therefore, the proper functional form should be used for the experimental data regression.
- Published
- 2024
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